As social and mobile technologies penetrate the enterprise, the rep's world will undergo a dramatic shift in how information is used to acquire customers, cross-sell, up-sell and manage renewals. Surfacing insights about your customer and prospects - already a challenging endeavor - becomes a seemingly insurmountable hurdle in the world of social networks and tablet devices.
Everyone accepts that an uninformed rep is an ineffective rep. Yet, even the most diligent and analytic reps face an inherent disadvantage relative to buyers in this 'information war'. Since buyers are typically working on only a single major purchase decision at a time, they can dive deep into research on vendor options, comparative product performance, peer buyer reviews and pricing. Unfortunately, sellers don't have this luxury as most B2B reps cover between 5 and 500 accounts. A B2B sales organization has two options when confronting this asymmetry:
- Provide reps with a generic pitch and accept the fact that they will have shallow, less insightful conversations with their customers, or
- Invest in an internal sales engineering/consulting function to create and deliver tailored pitches.
Option 1 reduces quality while Option 2 increases cost. Neither is an optimal approach in a world where it is becoming possible to know every salient detail about customers and prospects at ever lower costs.
Most organizations are ill-suited to handle this data-deluge and risk facing a reduction in sales rep productivity especially against the backdrop of a jittery global economy. The current process of generating useful information for reps will not scale as it relies on manual processes, excel spreadsheets, outdated systems, and an assumption of structured data. There are four main obstacles:
- CRM doesn't cut it: CRM was never designed to help the rep be more effective. While, it is a great tool for helping sales managers track rep-activity and forecast performance, the application is not dynamic enough to source, aggregate and deliver information to reps in a real-time, relevant manner.
- Internal customer data systems are outdated: Organizations often go through heroic 'data-warehousing' efforts to create a single view of the customer. Unfortunately, none of these systems anticipated the rise of social networks and the embedded unstructured data, or mobile apps and the real-time, location-based data they generate. These systems lack both the data-integration capability to pull real-time information from multiple sources - both internal and external - as well as the learning engine to turn data into insights that a rep could consume.
- Most interesting data-sources are increasingly unstructured: As companies 'tweet' and reps 'chat', the most interesting data is increasingly unstructured. For example, a tweet containing "we just opened our 1st office in Europe" cannot be neatly matched, aggregated, filtered or summarized in a spreadsheet (vs. structured data like revenue, employees, etc.)
- Manual processes do not scale: A number of forward-thinking companies have built analytical processes that require manual handling of data in a batch mode. This approach works fairly well for reporting. But a rep sitting in a customer's lobby before a meeting does not want yesterday's (or worse, last week's) news delivered today.
With less selling time, and ever larger data haystacks, it is no surprise that reps are having a harder time finding the right needles of insight. As a result, they often find themselves with no compelling business-driven reason to call their accounts, and resort to making ineffective outreaches that don't lead to increased pipeline or closed deals.
Fortunately, there is a better way. Forward thinking organizations can enable their reps to make data-driven selling decisions with the following six capabilities:
- Automate insight generation: With increasing data volumes, it will be impossible to manually identify and deliver customer insight to reps. The appending, aggregating, integrating and mining of raw data have to be automated to a point where manual intervention is required only when something breaks down
- Mine structured and unstructured data: Techniques for analyzing and mining unstructured data are still being developed. However, Natural Language Processing (NLP) has made major strides in the last few years, thanks to web-scale data efforts. By focusing just on what is easy (structured analysis), organizations are missing out on what is valuable (unstructured analysis).
- Roll with the medium: Each new source of information comes with its own possibilities and constraints. Tweets can be mined to understand a buyer's interests. Emails can be mined to understand patterns in communication that reflect higher likelihoods of closing deals. Mobile data can be mined to automatically populate CRM activity. But mining all of the new sources means that the analyst has to be conversant in multiple techniques, each of which are evolving at a rapid pace.
- Infer best-practices: The best reps are already using information in interesting ways. Passive data generated by the use of sources, call logs or trails left from a Mobile application can be used to infer what activities and behaviors increase the likelihood of close. These best-practices can then be automatically routed to struggling reps.
- Test and Learn: As you add new sources of information, you will find that reps don't engage equally well on all of them. Give them a chance to provide feedback and retire sources that don't add tangible value to improving their sales outcomes.
- Focus on performance: Remember that everything you do is to help the rep perform better. Best-in-class companies track both effort metrics (e.g., calls/day or time spent selling) as well as outcomes (e.g., Sales or Renewal rate). If these efforts are not helping a rep perform better, step back and ask why?
We at Lattice Engines are investing simultaneously across all these fronts to improve the effectiveness of the rep. As we work with our customers, we are learning about what works and what doesn't, what is useful and what isn't and what ultimately helps the individual rep.
Is there something that we have missed? We would love to hear from you.